| import gradio as gr |
| from huggingface_hub import InferenceClient |
| import os |
|
|
| api_key = os.environ.get('qwen_API_KEY') |
| """ |
| For more information on huggingface_hub Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference |
| """ |
| client = InferenceClient( token=api_key) |
|
|
| def respond( |
| message, |
| history: list[tuple[str, str]], |
| system_message, |
| max_tokens, |
| temperature, |
| top_p |
| ): |
| messages = [{"role": "system", "content": system_message}] |
|
|
| for val in history: |
| if val[0]: |
| messages.append({"role": "user", "content": val[0]}) |
| if val[1]: |
| messages.append({"role": "assistant", "content": val[1]}) |
|
|
| messages.append({"role": "user", "content": message}) |
|
|
| response = "" |
|
|
| for message in client.chat_completion( |
| messages, |
| model="Qwen/Qwen2.5-72B-Instruct", |
| max_tokens=max_tokens, |
| stream=True, |
| temperature=temperature, |
| top_p=top_p |
| ): |
| token = message.choices[0].delta.content |
|
|
| response += token |
| yield response |
| |
| example_prompts = [ |
| ["泰语的起源?", "你是一个歌词助手"], |
| ["你是谁开发的?", "你是一个歌词助手"], |
| ["写一篇关于青春的五言绝句", "你是一个歌词助手"], |
| ["你是谁?", "你是一个歌词助手"] |
| ] |
| latex_delimiters = [ |
| {"left": "$$", "right": "$$", "display": True}, |
| {"left": "\\[", "right": "\\]", "display": True}, |
| {"left": "$", "right": "$", "display": False}, |
| {"left": "\\(", "right": "\\)", "display": False} |
| ] |
|
|
| demo = gr.ChatInterface( |
| fn=respond, |
| examples=example_prompts, |
| cache_examples=False, |
| title="Qwen2.5-72B-Instruct", |
| description="千问2.5-72B聊天机器人", |
| additional_inputs=[ |
| gr.Textbox(value="You are a helpful assistant.", label="System message"), |
| gr.Slider(minimum=1, maximum=8888, value=2048, step=1, label="Max new tokens"), |
| gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"), |
| gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"), |
| ], |
| chatbot=gr.Chatbot(show_label=True, latex_delimiters=latex_delimiters, show_copy_button=True) |
| ) |
|
|
| if __name__ == "__main__": |
| demo.queue(default_concurrency_limit=60) |
| demo.launch(max_threads=60) |